code: def test_parameter_saved() -> None:
      dtype = tf.float64
  
      class Model(tf.Module):
          def __init__(self) -> None:
              self.p = gpflow.Parameter(
                  0.1,
                  dtype=dtype,
                  transform=gpflow.utilities.positive(),
              )
  
          @tf.function(input_signature=[tf.TensorSpec([], dtype=dtype)])
          def exec(self, x: tf.Tensor) -> tf.Tensor:
              return tf.square(x * self.p)
  
      m0 = Model()
      x = tf.convert_to_tensor(2.0, dtype=dtype)
      expected = m0.exec(x)
      with tempfile.TemporaryDirectory() as dirname:
          tf.saved_model.save(m0, dirname)
          m1 = tf.saved_model.load(dirname)
          actual = m1.exec(x)
          np.testing.assert_equal(actual, expected)
  
imports: import tempfile
  from typing import Sequence
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  import gpflow
  from gpflow.base import AnyNDArray, PriorOn, TensorData
  from gpflow.config import default_float
  from gpflow.utilities import positive, triangular
label_desc: Use image node_id 3 for calling a global function with example usage: test_parameter_saved() and returns: tf